Hamid, Anis

PURPOSE The continuous development of new imaging approaches, molecular phenotyping, genetic subtypes, prognosis assessments, and effective therapies across a range of disease states has created a need to redefine terminology and best practices for clinical trial conduct in patients with advanced prostate cancer. Methods We convened an international expert committee of diverse working groups, the Prostate Cancer Working Group 4 (PCWG4), between 2016 and 2025. Our objective was to formulate updated criteria based on emerging evidence and clinical trial data in a biomarker context to provide guidance for clinical trial design, eligibility, and end point assessments for patients with advanced prostate cancer. RESULTS PCWG4 redefines terminology around the disease state and previous therapies in a patient-centric context and terminology focused on androgen pathway modulation. We consider imaging, with a particular focus on positron emission tomography (PET)–defined disease. New recommendations are provided for disease state terminology, defining eligibility criteria, response and delay/prevent end points, intervals for reassessments including imaging, and patient-reported outcome determination. We provide recommendations in a biomarker-based context of use for the intended indication, reflective of patient benefit for specific interventions. We emphasize the need for development of validated PET imaging and molecular and phenotypic criteria as well as trial designs to appropriately risk stratify patients, predict and assess benefit, and measure post-treatment outcomes reliably in a trial framework. CONCLUSION PCWG4 updates recommendations on patient and tumor characterization, therapy development, and imaging criteria and extends guidance into earlier androgen pathway modulator–naïve/sensitive disease states to reflect an evolving, heterogeneous, and diverse patient population to optimize treatment benefits for all patients.

AbstractBackgroundProstate cancer (PCa) is a clinically heterogeneous disease. The creation of an expression‐based subtyping model based on prostate‐specific biological processes was sought.MethodsUnsupervised machine learning of gene expression profiles from prospectively collected primary prostate tumors (training, n = 32,000; evaluation, n = 68,547) was used to create a prostate subtyping classifier (PSC) based on basal versus luminal cell expression patterns and other gene signatures relevant to PCa biology. Subtype molecular pathways and clinical characteristics were explored in five other clinical cohorts.ResultsClustering derived four subtypes: luminal differentiated (LD), luminal proliferating (LP), basal immune (BI), and basal neuroendocrine (BN). LP and LD tumors both had higher androgen receptor activity. LP tumors also had a higher expression of cell proliferation genes, MYC activity, and characteristics of homologous recombination deficiency. BI tumors possessed significant interferon γactivity and immune infiltration on immunohistochemistry. BN tumors were characterized by lower androgen receptor activity expression, lower immune infiltration, and enrichment with neuroendocrine expression patterns. Patients with LD tumors had less aggressive tumor characteristics and the longest time to metastasis after surgery. Only patients with BI tumors derived benefit from radiotherapy after surgery in terms of time to metastasis (hazard ratio [HR], 0.09; 95% CI, 0.01–0.71; n = 855). In a phase 3 trial that randomized patients with metastatic PCa to androgen deprivation with or without docetaxel (n = 108), only patients with LP tumors derived survival benefit from docetaxel (HR, 0.21; 95% CI, 0.09–0.51).ConclusionsWith the use of expression profiles from over 100,000 tumors, a PSC was developed that identified four subtypes with distinct biological and clinical features.Plain language summary Prostate cancer can behave in an indolent or aggressive manner and vary in how it responds to certain treatments. To differentiate prostate cancer on the basis of biological features, we developed a novel RNA signature by using data from over 100,000 prostate tumors—the largest data set of its kind. This signature can inform patients and physicians on tumor aggressiveness and susceptibilities to treatments to help personalize cancer management.

241 Background: We previously reported on the use of gene expression profiling to characterize four primary subtypes in an analysis of over 100,000 prostate cancer primary tumors. Here we examine these subtypes and response to radiation (RT) after prostatectomy or chemotherapy in addition to androgen deprivation therapy (ADT) in hormone-sensitive metastatic prostate cancer (mHSPC). Methods: We examined a 215-gene prostate subtyping classifier (PSC) which groups luminal and basal gene expression profiles into one of four subtypes; luminal differentiated (LD), luminal proliferating (LP), basal immune (BI) and basal neuroendocrine-like (BN). The log-rank method was used to compare (i) metastasis-free survival between patients who did and did not receive salvage RT in the META855 cohort of localized disease patients treated with radical prostatectomy (n=855) and the (ii) overall survival of patients on the Phase III mHSPC EA3805 CHAARTED trial of ADT or ADT + docetaxel chemotherapy (n=160). Results: After radical prostatectomy, patients with BI tumors derived benefit from RT in terms of metastasis-free survival ( P=9.23e-4) while those with other subtype tumors did not (Each Log-rank P≥0.5). Patients with metastatic disease and LP tumors derived benefit from docetaxel (Log-rank P=0.002) while those with other subtypes tumors did not (Log-rank P=0.2). Conclusions: Basal-luminal subtyping segments tumors by relevant biological processes with potential implications for identifying patients who benefit from salvage radiation post prostatectomy and addition of docetaxel to ADT in mHSPC.